- Autonomous Vehicles - Home
- Autonomous Vehicles - Introduction
- Autonomous Vehicles - Types
- Autonomous Vehicles - Needs
- Autonomous Vehicles - Advantages
- Autonomous Vehicles - Possible Impact
- Autonomous Vehicles - Levels of Autonomy
- Autonomous Vehicles - Technology
- Autonomous Vehicles - Risks
- Autonomous Vehicles - Applications
Autonomous Vehicles - Technology
Autonomous vehicles or self-driving cars use a wide range of advanced technologies to perform driving tasks without any human intervention or assistance. Thus, these vehicles are completely dependent on various technologies that work together to perform control, monitoring, and decision-making functions on the roads.
In this chapter, we will discuss about each technology used in autonomous or self-driving vehicles.
Technology inside Autonomous Vehicles
The following are some key technologies behind the autonomous working of a self-driving car −
Advanced Sensors
Sensors act as the eyes and ears of the autonomous vehicles. In autonomous vehicles, a variety of advanced sensors are used to collect data from the surrounding environment. These sensors help the vehicle to understand its surrounding elements like other vehicles, obstacles, road signs, pedestrians, etc.
The following are some primarily used types of sensors in an autonomous vehicle −
LiDAR
LiDAR stands for Light Detection and Ranging. LiDAR is a laser-based sensor technology that used in autonomous vehicles to create a 3D map of the surrounding environment. This sensor allows the vehicles to identify nearby objects and measure their distance from the vehicle.
LiDAR is known for its high accuracy and depth perception and it is very helpful in detecting objects at night or in bad weather conditions. However, it is a very expensive sensor technology and does not work properly in heavy rain or snow fall conditions.
RADAR
RADAR stands for Radio Detection and Ranging. It is also a sensor technology that makes use of radio waves and is used in autonomous vehicles to detect the position and speed of nearby objects like other vehicles on the road.
The most significant benefit of the RADAR technology is that it can work well in most weather conditions and is capable in measuring speed of moving vehicles in the surrounding environment of the autonomous vehicle.
However, due to limited resolution, RADAR may not be able to detect small objects. It is also less accurate in recognizing specific shapes of objects.
Cameras
Cameras are used in autonomous vehicles to allow them to see the surrounding environment. They are responsible for detecting road signs, traffic lights, lane markings, and other road infrastructure components.
Cameras are capable in providing detailed images of the surrounding and are also less expensive than LiDAR and RADAR. However, they do not work properly in low light, rain, fog, and other poor weather conditions. Additionally, complex algorithms are required for accurate interpretation of visual data captured by cameras.
Ultrasonic Sensors
Ultrasonic sensors work by emitting sound waves and used to detect objects in a short and closed range like in parking space. These sensors are used in autonomous vehicle to perform functions like auto-parking. These sensors are less expensive but they work withing a limited range.
Artificial Intelligence (AI) and Machine Learning
Artificial intelligence and machine learning act as the brain of the autonomous vehicle and perform functions like decision making, self-learning from actions, understanding surroundings, etc.
Autonomous vehicles use AI-based neural network that process and interpret data captured by sensors. AI allows autonomous vehicles to identify objects, make predictions and decisions, plan and control the movements of vehicle, etc. Overall, AI and machine learning help the autonomous vehicles to make real-time decisions accurately.
However, AI and machine learning are data-based technologies and require a large amount of data to make decisions and release commands.
Computer Vision
Computer vision is also a part of artificial intelligence which involves tasks like image and video processing. It is used in autonomous vehicles to process camera's visual data to understand the surrounding environment.
Computer vision allows autonomous vehicles to identify obstacles, lane markings, and traffic signs and signals. It is responsible for ensuring accurate movements of the vehicle and provide safe autonomous driving even in a complex environment.
However, this technology requires advanced hardware and complex programs to handle unexpected events and poor visibility conditions.
GPS and Maps
Autonomous vehicles need precise data about locations and routes to navigate accurately. This data is provided by GPS (Global Positioning System) and high-definition maps.
GPS is a satellite-based system that integrated into autonomous vehicles to determine their exact locations. It is also integrated with high-definition maps to help the vehicle understand where it is and identify optimized routes. Although, the GPS system becomes less accurate in congested urban areas or in tunnels due to signal blockage.
The high-definition maps provide a detailed layout of roads and the infrastructure along with information about lane markings, traffic signals and signs, etc. Maps are essential for planning optimized routes and safely navigate the vehicle. However, the rapid infrastructure changes require updating the maps which is a challenging and costly task.
Vehicle-to-Everything (V2X) Communication
Communication or connectivity is one of the most crucial technologies in autonomous vehicles. It allows vehicles to communicate and exchange data and information with other vehicles, road infrastructure and servers.
In autonomous vehicles, there are several different types of communications used, such as vehicle-to-vehicle communication, vehicle-to-infrastructure communication, communication with cloud servers.
The vehicle-to-vehicle (V2V) communication allows autonomous vehicles to share information like speed, direction, etc. with other vehicles. It is responsible for providing a safe navigation on roads.
The vehicle-to-infrastructure (V2I) communication allows vehicles to communicate with infrastructure components like road signs, traffic signals, etc. This communication ensures better traffic management and reduces congestion on roads. However, it is very challenging and expensive to implement because it requires major changes in the existing infrastructure.
Cloud connectivity or communication with cloud servers enable autonomous vehicles to access maps, location details, and traffic updates. This communication ensures that the vehicles are up-to-date with the latest information. Although, this communication is subjected to network failures and connectivity issues that could disturb the vehicle operations and impact the road safety.
Path Planning System
It is a software component of the autonomous vehicle that helps planning the optimized routes and provides directions to navigate safely. This system is crucial for smooth and safe driving of the vehicle autonomously.
Motion Control System
In autonomous vehicles, the motion control system receives input from AI system and performs actions like steering, acceleration, braking, etc. accordingly. This system is responsible for providing precise control for safe and smooth operation of the vehicle.
Edge Computing
Autonomous vehicles require real-time data processing to perform actions quickly. Edge computing enables them to do so. This technology implements capabilities in the autonomous vehicle to process data locally without being relying on the cloud server. Edge computing plays an important in reducing delay and makes the autonomous vehicles faster in decision-making.
Cybersecurity Systems
Autonomous vehicles use advanced connectivity, software, and data, which are vulnerable to cyberthreats. Hence, cybersecurity systems like encryption, firewalls, intrusion detection systems, etc. are used in these vehicles to protect them from all kinds of cyber threats. These systems are essential for protecting the vehicles sensitive data and hacking.
Conclusion
Autonomous vehicles are an interesting blend of various advanced technologies that enable these vehicles to see, think, and take actions, without need for any human driver. Each of these technologies play an important role in self-driving of these vehicles safely.